About the job
Join us in revolutionizing how billions of users interact with their most critical information within Google Workspace. Our team is at the heart of Workspace's artificial intelligence (AI) transformation, building the intelligent, agentic layer that deeply understands and acts upon user needs across Gmail, Drive, Calendar, Chat, and beyond. In this role, you will manage the exciting issues of creating Generative Artificial Intelligence agents that can semantically search, reason over, and synthesize information from Workspace sources to provide direct, high-quality answers and power sophisticated, personalized workflows.
Responsibilities
Provide technical leadership on high-impact projects.
Influence and coach a distributed team of engineers.
Clarify and solve ambiguous technical issues by collaborating with leadership and cross-functional partners to integrate Agentic infrastructure.
Partner with Workspace vertical teams to drive engineering excellence, proactively anticipating scaling bottlenecks to ensure low-latency performance and reliability.
Develop the technical goals and roadmap for our Agentic future, exhibiting strong judgment in balancing immediate product needs with the long-term health of our autonomous protocols.
Qualifications
Minimum
Bachelor's degree or equivalent practical experience.
8 years of experience in software development in one or more programming languages (e.g., C++, Python).
5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
Preferred
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
8 years of experience with data structures and algorithms.
3 years of experience in a technical leadership role leading project teams and setting technical direction.
Experience developing agentic systems, including multi-agent architectures, Model Context Protocol (MCP) integration, and benchmarking for agentic reliability and safety (e.g., AgentBench, CLEAR).